The Rational Selection of Goal Operations and the Integration ofSearch Strategies with Goal-Driven Autonomy
Kondrakunta, Sravya, Gogineni, Venkatsampath Raja, Cox, Michael T., Coleman, Demetris, Tan, Xiaobao, Lin, Tony, Hou, Mengxue, Zhang, Fumin, McQuarrie, Frank, Edwards, Catherine R.
–arXiv.org Artificial Intelligence
Intelligent physical systems as embodied cognitive systems must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and control must manage the problem of converting continuous values from the real world to symbolic representations (and back). To generate effective behaviors, reasoning must include a capacity to replan, acquire and update new information, detect and respond to anomalies, and perform various operations on system goals. But, these processes are not independent and need further exploration. This paper examines an agent's choices when multiple goal operations co-occur and interact, and it establishes a method of choosing between them. We demonstrate the benefits and discuss the trade offs involved with this and show positive results in a dynamic marine search task.
arXiv.org Artificial Intelligence
Jan-21-2022
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